In either an industrial or commercial setting, a malfunctioning imaging machine can impair a business severely. Thus, it is essential that a malfunctioning imaging machine be repaired quickly and accurately. Usually, during a malfunction of an imaging machine such as an ultrasound, computed tomography (CT), or a magnetic resonance imaging (MRI) machine, a field engineer is called in to diagnose and repair the machine. Typically, the field engineer looks at an incident record generated from the machine. The incident record contains information such as the type of machine, the modality of the machine, and any customer-related information. In addition, the incident record contains an error log of events that occurred during routine operation as well as during any malfunction situation and any artifact images generated from the machine. Using their accumulated experience at solving machine malfunctions, the field engineer looks through the error log and the artifact images and tries to find any symptoms that may point to the fault. Then the field engineer tries to correct the problem that may be causing the machine malfunction. If the error log contains only a small amount of information, and the generated artifact images are well known, then this process will work fairly well. However, if the error log contains a large amount of imprecise information and the cause of the artifact images is unknown, as is usually the case for large complex devices, then it will be very difficult for the field engineer to quickly diagnose a fault. Therefore, there is a need for a system and method that can quickly diagnose a machine malfunction from a complex error log and artifact images having an unknown cause associated therewith.